Social Media Use and Health and Well-being of Lesbian, Gay, Bisexual, Transgender, and Queer Youth: Systematic Review
Notice bibliographique
Résumé
BACKGROUND: Lesbian, gay, bisexual, transgender, and queer (LGBTQ) individuals are at higher risk of poor mental health and well-being. Social media platforms can provide LGBTQ youths with a space that counters heteronormative environments and potentially supports mental health and well-being. Mental health includes an individual's state of psychological and emotional well-being and not merely the absence of mental disorders. OBJECTIVE: We sought to identify how LGBTQ youths and adolescents use social media for connection with other LGBTQ peers and groups, identity development, and social support and how these affect mental health and well-being. METHODS: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) procedures were used to guide this review. Searches were conducted in ACM Digital Library, CINAHL, Ovid Embase, Ovid MEDLINE, and Web of Science in March 2021. This review focused on LGBTQ youths aged 10 to 24 years. Included peer-reviewed studies must comprise social media; explore peer connection, identity development, or social support; and be published from 2012 onward. In total, 2 researchers extracted data and performed quality assessments independently using the Newcastle-Ottawa Scale for quantitative articles and the Critical Appraisal Skills Programme for qualitative articles. Qualitative synthesis was performed on articles that satisfied the eligibility criteria. RESULTS: A total of 26 studies (n=15, 58% qualitative; n=8, 31% quantitative; n=3, 12% mixed methods) met the inclusion criteria. Of the 8 quantitative studies, 6 (75%) were cross-sectional, and 2 (25%) were cohort studies. All studies ranged from moderate to high quality. Social media was a popular tool used by LGBTQ youths to connect with LGBTQ communities. In qualitative data, we found that LGBTQ youths negotiated and explored identity and obtained support from peers on social media. Instagram, Tumblr, and Twitter were commonly used to access LGBTQ content owing to ease of anonymity. Identity management was the most studied social media affordance, important to LGBTQ youths for strategic disclosure. Key strategies for managing identities included being anonymous, censoring locations or content, restricting audiences, and using multiple accounts. Quantitative studies (3/8, 38%) showed that social media was associated with reduced mental health concerns and increased well-being among LGBTQ youths. Mental health concerns arising from social media use were attributed to discrimination, victimization, and policies that did not accommodate changed identities. CONCLUSIONS: We found that social media may support the mental health and well-being of LGBTQ youths through peer connection, identity management, and social support, but findings were limited by weaknesses in the evidence. More robust and longitudinal studies are needed to determine the relationship between social media use and LGBTQ mental health, particularly among adolescents. The findings may inform interventions to promote social media health literacy and the mental health and well-being of this vulnerable group. TRIAL REGISTRATION: PROSPERO CRD42020222535; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=222535.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,007 | 0,007 |
| Bibliométrie | 0,009 | 0,011 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».